Lead, World Models ML Engineer — Physical AI

Engg; San Francisco (CA); On-site; USD 200,000 - 260,000; Full time

Job summary

Atoms is seeking a Senior Staff Machine Learning Engineer focused on World Models to join our AI organization in San Francisco. You will shape foundation model strategies for physical AI, integrating multimodal data from video, images, sensor streams, and robot state to learn representations of real-world environments.

You’ll lead architectural decisions, mentor researchers, and translate cutting-edge research into deployable systems that operate on real machines in real environments.

Qualifications

• Deep expertise in machine learning and DL foundation models.
• Experience with multimodal learning and video models.
• Track record of translating research into ML systems.
• Strong Python and modern ML frameworks.
• Ability to work in ambiguous research spaces.

Responsibilities

• Define and build architecture for world models and foundation models.
• Develop large-scale models learning representations of dynamic physical environments.
• Collaborate with research and engineering across robotics and AI.
• Translate research into real-world machine deployments.
• Establish evaluation methodologies for physical world understanding.

Skills

Foundation models

Multimodal learning

Embodied AI

Large-scale DL systems

Python

Education

PhD in ML or related field

Tools

PyTorch

TensorFlow

Job description

Atoms is seeking a Senior Staff Machine Learning Engineer focused on World Models to join our AI organization in San Francisco. You will shape foundation model strategies for physical AI, integrating multimodal data from video, images, sensor streams, and robot state to learn representations of real-world environments.

You’ll lead architectural decisions, mentor researchers, and translate cutting-edge research into deployable systems that operate on real machines in real environments.